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Stable inversion method for a polarized-lidar: analysis and simulation.

H Wei1, R Koga, K Iokibe

  • 1Graduate School of Natural Science and Technology, Okayama University, Tsushima, Japan.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|February 24, 2001
PubMed
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A novel inhomogeneous atmosphere (IA) method offers improved stability for analyzing polarized Mie lidar signals. This new approach enhances precision in calculating atmospheric properties like backscattering and extinction-to-backscattering ratio (EBR).

Area of Science:

  • Atmospheric optics
  • Lidar remote sensing
  • Aerosol and molecular scattering

Background:

  • Accurate retrieval of atmospheric properties from lidar signals is crucial for climate and air quality studies.
  • Existing methods, like Fernald's, face limitations in stability and precision, especially for complex atmospheric conditions.
  • Polarized Mie lidar provides valuable information on particle size, shape, and composition, but requires sophisticated retrieval algorithms.

Purpose of the Study:

  • To introduce and validate a new, more stable inversion method for analyzing two-component (molecule and aerosol) scattering from polarized Mie lidar signals.
  • To demonstrate the capability of the new method to calculate the backscattering coefficient and extinction-to-backscattering ratio (EBR) without additional assumptions in specific atmospheric regions.
  • To compare the performance of the proposed inhomogeneous atmosphere (IA) method against the established Fernald's method using both simulations and experimental data.

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Main Methods:

  • Development of a new inversion algorithm for inhomogeneous atmospheres (IA) applicable to polarized Mie lidar data.
  • Extension of the inversion procedure to incorporate both inward and outward stepwise integration algorithms.
  • Validation through numerical simulations to assess precision in estimating boundary values and EBR.
  • Experimental verification using real-world lidar measurements to compare with Fernald's method.

Main Results:

  • The proposed IA method demonstrates superior stability compared to Fernald's method for two-component scattering analysis.
  • The IA method enables the calculation of backscattering coefficient and EBR in regions with depolarization ratios lower than molecular values, without further assumptions.
  • Simulation results show higher precision with the IA method, exhibiting reduced error and random noise in boundary value and EBR estimations.
  • Experimental results confirm the improved performance of the IA method over Fernald's method.

Conclusions:

  • The inhomogeneous atmosphere (IA) inversion method provides a more stable and precise alternative to Fernald's method for polarized Mie lidar signal analysis.
  • This advancement allows for more reliable retrieval of atmospheric optical properties, particularly the backscattering coefficient and EBR.
  • The IA method's enhanced accuracy holds significant implications for atmospheric research, climate modeling, and air quality monitoring.